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» Globally Induced Model Trees: An Evolutionary Approach
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ICML
2004
IEEE
16 years 13 days ago
Lookahead-based algorithms for anytime induction of decision trees
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
AAAI
2006
15 years 1 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
EMMCVPR
2001
Springer
15 years 4 months ago
Matching Free Trees, Maximal Cliques, and Monotone Game Dynamics
—Motivated by our recent work on rooted tree matching, in this paper we provide a solution to the problem of matching two free (i.e., unrooted) trees by constructing an associati...
Marcello Pelillo
SIAMCOMP
1998
111views more  SIAMCOMP 1998»
14 years 11 months ago
Computing the Local Consensus of Trees
The inference of consensus from a set of evolutionary trees is a fundamental problem in a number of fields such as biology and historical linguistics, and many models for inferrin...
Sampath Kannan, Tandy Warnow
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 3 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace